Recently, convenient and efficient three-dimensional reconstruction of scenes or objects has become a research focus, more and more three-dimensional imaging techniques are constantly emerging, and for the sake of realistic three-dimensional images, it is necessary to calculate the depth information of scenes or objects, which means that depth perception is required. As the core technology of three-dimensional reconstruction, the depth perception technology has broad application and development prospects in the fields such as machine vision, man-machine interaction, 3D printing, virtual reality, smart phones and the like.
The existing depth perception technology based on structured-light encoding and decoding can acquire accurate depth information without being affected by ambient light, algorithms or hardware and can be easily, conveniently and rapidly implemented in such a manner that a constant image is projected to the surface of an object with infrared lasers and is reflected by the surface of the object to form speckles and these speckles are acquired by an image sensor and then calculated by an image depth perception chip to obtain the depth information of the object. 3D depth cameras based on the structured-light encoding and decoding technology have a simple three-dimensional matching process and a small amount of calculation; however, in order to obtain high-precision depth information, high assembly precision of the 3D depth cameras should be ensured, and once the optical axis of a laser image projector or an image sensor deflects in use due to falling or collision, the depth precision will decrease, and the mismatch noise will increase. Particularly for structured-light 3D depth cameras embedded in smart phones, falling, collision and knocking can hardly be avoided when the smart phones are used by users, which is quite likely to result in distortion of the optical axes of the structured-light depth cameras. For this reason, it is of particular importance to develop an automatic collection technique for the structured-light 3D depth cameras to avoid precision reduction and noise increase caused by optical axis changes and to improve the robustness of the structured-light 3D depth cameras.